Job Description

AI Solution Tech Lead

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Key Responsibilities

· Technical Ownership Thru Application Lifecycle

- The Lead Software Engineer is responsible for design, build, deployment and maintenance of tailor-made and/or software packages or the adaptation of existing ones.

- Provides day-to-day application support: Possess good initiative, be able to actively follow up on online issues, and do a good job of sustaining as daily duty.

- Complex malfunctions, incidents and bugs are managed, understood, analyzed, reported and solved.​

- Continuous study, analyze and manage the code, scripts, and other assets, and ensure compatibility with overall product and architecture strategy.

· Key player in solution implementation

- The business needs are analyzed and converted into functional and/or technical specifications

- Act as key player in solution implementation, deliver the core modules and handle complex technical challenges, including model selection, deployment options, context engineering, Retrieval-Augmented Generation (RAG), AI agents etc

- Major changes to existing applications are implemented. Technical support by diagnosing and solving complex incidents is guaranteed. Complex technical questions are answered.

· Technical Quality & Excellence

- Ensuring the non-functional system qualities: stability, scalability, performance, security and consistency.

- Ensure code quality (Readability, Maintainability, Efficiency, Reliability, Testability) by defining and cascading developer guidance, proceeding code review.

- Adopt quality gate, automation test or other quality related standard in CI/CD pipeline.

· Technology Leadership & Innovation

- Stay up to date with cutting-edge technologies, particularly in adopting AI into technical solutions & development.

- Experiment with new frameworks, architectures, and methodologies

- Promote engineering AI best practices within the team to improve development efficiency and code quality.

Qualifications

- Bachelor’s or above degree in computer science or related field.

- 5+ years of experience in software engineering, including hands-on experience in AI-related or data-intensive applications.

- Speak and write in both English and Chinese.

- Proven track record of delivering end-to-end, production-grade AI system solutions

Technical Skill

- Solid in Pythoncoding, with Sophisticated in adopting principles: (modular design, DRY, testability).

- Practical knowledge in AI-oriented development frameworks such as LangChain, LangGraph, or similar orchestration tools.

- Good knowledge & practical experience in Elasticsearch, Redis, Kafka, Kubernetes, CI/CD, Postgresql/Mysql, cloud-based hosting, monitoring and alerting.

- Analytical Skills: Strong analytical and problem-solving abilities, with a proven track record of tackling complex technical challenges.

- Familiarity with major foundation models (e.g., GPT, Qwen) and ability to evaluate AI component suitability is a plus.

Soft Skills & Behavioral Traits

· Curiosity & Fast Learning: A strong desire to learn and rapidly apply new technologies and methodologies.

· Innovative Thinking: Creativity in proposing technical solutions to complex business problems and thinking outside the box.

· Communication Skills: sufficient ability of active listening and translating complex technical concepts into clear, business-friendly language for stakeholders.

· Problem-solving mindset with a focus on delivering practical technical solutions that drive real business outcomes.

· Intrinsic motivation to contribute to customer value and company success with willingness to take responsibilities beyond the role and assigned tasks.

· Experience with AI-assisted programming tools (e.g., Cursor, GitHub Copilot, Codeium), and ability to leverage them effectively to improve development productivity and code quality.